Tracing COVID-19 Infection Chains Within Healthcare Institutions – Another Brick in the Wall Against SARS-CoV-2
Antje Wulff, Pascal Biermann, Tatiana von Landesberger, Tom Baumgartl, Christoph Schmidt, Alan Yussef Alhaji, Kristina Schick, Paul Waldstein, Yufei Zhu, HiGHmed Infection Control Study Group, Dagmar Krefting, Simone Scheithauer, Michael Marschollek
Early anticipation of COVID-19 infection chains within hospitals is of high importance for initiating suitable measures at the right time. Infection control specialists can be supported by application systems able of consolidating and analyzing heterogeneous, up-to-now non-standardized and distributed data needed for tracking COVID-19 infections and infected patients’ hospital contacts. We developed a system, Co-Surv-SmICS, assisting in infection chain detection, in an open and standards-based way to ensure reusability of the system across institutions. Data is modelled in alignment to various national modelling initiatives and consensus data definitions, queried in a standardized way by the use of OpenEHR as information modelling standard and its associated model-based query language, analyzed and interactively visualized in the application. A first version has been published and will be enhanced with further features and evaluated in detail with regard to its potentials to support specialists during their work against SARS-CoV-2.
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